Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- List of panels
- Preface
- Part I Elementary statistical analysis
- Part II Samples and inductive statistics
- Part III Multiple linear regression
- Chapter 8 Multiple relationships
- Chapter 9 The classical linear regression model
- Chapter 10 Dummy variables and lagged values
- Chapter 11 Violating the assumptions of the classical linear regression model
- Part IV Further topics in regression analysis
- Part V Specifying and interpreting models: four case studies
- Appendix A The four data sets
- Appendix B Index numbers
- Bibliography
- Index of subjects
- Index of names
Chapter 9 - The classical linear regression model
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- List of figures
- List of tables
- List of panels
- Preface
- Part I Elementary statistical analysis
- Part II Samples and inductive statistics
- Part III Multiple linear regression
- Chapter 8 Multiple relationships
- Chapter 9 The classical linear regression model
- Chapter 10 Dummy variables and lagged values
- Chapter 11 Violating the assumptions of the classical linear regression model
- Part IV Further topics in regression analysis
- Part V Specifying and interpreting models: four case studies
- Appendix A The four data sets
- Appendix B Index numbers
- Bibliography
- Index of subjects
- Index of names
Summary
This chapter builds on our previous work and takes a succession of giant strides towards realistic quantitative analysis of relationships between two or more variables. After completing this material it will be possible to examine a large range of potential historical problems, and to read critically many of the studies in history and the social sciences that make use of regression and related quantitative techniques.
We will begin in §9.1 with a brief discussion of the concept of a ‘model’ and of the associated methodology of quantitative research into the relationships between two or more variables. The basic technique of linear regression (discussed in chapters 4 and 8) is then extended in §9.2 to examine the reasons why the observed values of the dependent variable deviate from the regression line, and to consider the implications of these deviations. In §9.3 a new test statistic, the F-test, is introduced and used to test the significance of the multiple regression as a whole. Finally, §9.4 is devoted to a further useful summary statistic, the standard error of the estimate.
Historical research and models of relationships between variables
One of the principal features of quantitative research in the historical and social sciences is the attempt to analyse and explain the behaviour of some particular variable.
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- Making History CountA Primer in Quantitative Methods for Historians, pp. 258 - 279Publisher: Cambridge University PressPrint publication year: 2002